Brain Tumor MRI images have been classified into 4 classes by using Transfer Learning Models.

This project is a Steel Defect Detection System using a ResNet152V2-based deep learning model. The model predicts bounding boxes for steel defects in images and classifies them into multiple defect types. It is implemented using TensorFlow and Keras for the deep learning components.

This notebook has the model created to predict COVID-19 only based on X-ray chest scans.

'CNN_Sorghum_Weed_Classifier' is an artificial intelligence (AI) based software that can differentiate a sorghum sampling image from its associated weeds images.

Image classification

Klasifikasi Kanker otak dengan 7 model CNN

An End-to-End Pneumonia Diagnosis(from Chest X-Ray images) application built using Flask and Deep Learning models trained using TensorFlow on a Kaggle Dataset.

Eye Disease Detection using Transfer Learning (DenseNet-121, EfficientNetB3, VGG-16, Resnet-152)

Utilizing ResNet152V2 for Traffic Sign Classification: Achieve High Accuracy in Identifying 52 Sign Types with 99% Precision